Results 91 to 100 of about 35,174 (215)

A convolutional-recurrent neural network approach to resting-state EEG classification in Parkinson's disease. [PDF]

J Neurosci Methods, 2021
Lee S, Hussein R, Ward R, Jane Wang Z, McKeown MJ.   +4 more
europepmc   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

HybridMouse: A Hybrid Convolutional-Recurrent Neural Network-Based Model for Identification of Mouse Ultrasonic Vocalizations. [PDF]

Front Behav Neurosci, 2021
Goussha Y, Bar K, Netser S, Cohen L, Hel-Or Y, Wagner S.   +5 more
europepmc   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

A joint convolutional-recurrent neural network with an attention mechanism for detecting intracranial hemorrhage on noncontrast head CT. [PDF]

Sci Rep, 2022
Alis D, Alis C, Yergin M, Topel C, Asmakutlu O, Bagcilar O, Senli YD, Ustundag A, Salt V, Dogan SN, Velioglu M, Selcuk HH, Kara B, Ozer C, Oksuz I, Kizilkilic O, Karaarslan E.   +16 more
europepmc   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

CRNNTL: Convolutional Recurrent Neural Network and Transfer Learning for QSAR Modeling in Organic Drug and Material Discovery. [PDF]

Molecules, 2021
Li Y, Xu Y, Yu Y.
europepmc   +1 more source

Advances and Perspectives in Graphene‐Based Quantum Dots Enabled Neuromorphic Devices

Advanced Science, EarlyView.
Graphene‐based QDs are zero‐dimensional carbon nanomaterials with pronounced quantum confinement and tunable electronic structures. Herein, we summarize their synthesis strategies and functionalization methods, and highlight their functional roles and operating mechanisms in devices, as well as recent advances in neuromorphic electronics. We anticipate
Yulin Zhen, Wei Zeng, Zherui Zhao, JiYu Zhao, Ziyan Huang, Zhuo Chen, Kui Zhou, Guanglong Ding, Su‐Ting Han, Ye Zhou   +9 more
wiley   +1 more source

A convolutional recurrent neural network with attention framework for speech separation in monaural recordings. [PDF]

Sci Rep, 2021
Sun C, Zhang M, Wu R, Lu J, Xian G, Yu Q, Gong X, Luo R.   +7 more
europepmc   +1 more source

Sustainable Synaptic Device with Two‐Dimensional Ferroelectric Materials for Neuromorphic Computing

Advanced Science, EarlyView.
α‐In2Se3 based FeSFETs can be utilized as sustainable devices through polarization switching governed by both out‐of‐plane and in‐plane polarizations. Upon reaching a fatigued state, current annealing enabled by conductance modulation can significantly enhance the endurance of FeSFETs.
Jaewook Yoo, Seokjin Oh, Minah Park, Jong Min Song, Hongseung Lee, Seohyeon Park, Sojin Jung, Seongbin Lim, Soohyun Lim, Dongsun Shin, Ji Won Heo, TaeWan Kim, Hagyoul Bae   +12 more
wiley   +1 more source